Communication systems with multiple parallel physical channels have been widely deployed. Those parallel channels are achieved in time domain, i.e., each of the packets are transmitted in a different time slot, in the frequency domain such as orthogonal-frequency-division-multiplexing (OFDM) system, in a spatial domain such as the multiple-input multiple-output (MIMO) systems, respectively. With parallel channels, high throughput or high goodput can be achieved. On the other hand, a capability of throughput of more and more users also needs to be achieved in new wireless systems.
With more users, interference cannot be avoided if users share the same channels. The strong interference makes the receiver difficult to detect and decode the original messages, thus causes packet loss. Such collision between shared users on the same channel is also called jamming. Moreover, other channel impairments, e.g., deep fading, can also cause decoding failure and lead to packet loss. Another example for a parallel inference channel is a newly established cognitive radio system for reuse in the licensed spectrum in a new developing standard (IEEE 802.22). In such a system, the channels for secondary usage can be modeled as parallel channels, which suffer from strong interference from the primary users.
The packet loss due to jamming decreases throughput performance significantly. Anti-jamming coding techniques are then desired for recovering the lost packets to reduce the probability of packet loss and retransmission in parallel inference channels. One solution for anti-jamming is rateless coding. However, the rateless solution is not efficient for small redundancy or when the block length is not very large.
Accordingly, there is a need for an anti-jamming piecewise coding method for cognitive radio to improve the throughput efficiency with small redundancy and low complexity encoder and decoder.